AI Medical Compendium Topic:
Neoplasms

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Historical perspective and future directions: computational science in immuno-oncology.

Journal for immunotherapy of cancer
Immuno-oncology holds promise for transforming patient care having achieved durable clinical response rates across a variety of advanced and metastatic cancers. Despite these achievements, only a minority of patients respond to immunotherapy, undersc...

A facile approach to preparing personalized cancer vaccines using iron-based metal organic framework.

Frontiers in immunology
BACKGROUND: Considering the diversity of tumors, it is of great significance to develop a simple, effective, and low-cost method to prepare personalized cancer vaccines.

Deep-Learning-Based Nanomechanical Vibration for Rapid and Label-Free Assay of Epithelial Mesenchymal Transition.

ACS nano
Cancer is a profound danger to our life and health. The classification and related studies of epithelial and mesenchymal phenotypes of cancer cells are key scientific questions in cancer research. Here, we investigated cancer cell colonies from a mec...

Deep learning for automatic organ and tumor segmentation in nanomedicine pharmacokinetics.

Theranostics
: Multimodal imaging provides important pharmacokinetic and dosimetry information during nanomedicine development and optimization. However, accurate quantitation is time-consuming, resource intensive, and requires anatomical expertise. : We present ...

A D-Shaped Polymer Optical Fiber Surface Plasmon Resonance Biosensor for Breast Cancer Detection Applications.

Biosensors
Fiber-optic biosensors have garnered significant attention and witnessed rapid development in recent years owing to their remarkable attributes such as high sensitivity, immunity to electromagnetic interference, and real-time monitoring. They have em...

Generative adversarial network: a statistical-based deep learning paradigm to improve detecting breast cancer in thermograms.

Medical & biological engineering & computing
Thermography, as a harmless modality, thanks to its low equipment complexity in parallel with quick and cheap access, has been able to come up as a method with significant potential in the diagnosis of some cancers in recent years. However, the compl...

A computational tumor growth model experience based on molecular dynamics point of view using deep cellular automata.

Artificial intelligence in medicine
Cancer, as identified by the World Health Organization, stands as the second leading cause of death globally. Its intricate nature makes it challenging to study solely based on biological knowledge, often leading to expensive research endeavors. Whil...

Short-term and long-term efficacy in robot-assisted treatment for mid and low rectal cancer: a systematic review and meta-analysis.

International journal of colorectal disease
OBJECTIVE: This study aims to conduct a meta-analysis to evaluate the short-term and long-term therapeutic effects of robot-assisted laparoscopic treatment in patients with mid and low rectal cancer.

Advancing equitable and personalized cancer care: Novel applications and priorities of artificial intelligence for fairness and inclusivity in the patient care workflow.

European journal of cancer (Oxford, England : 1990)
Patient care workflows are highly multimodal and intertwined: the intersection of data outputs provided from different disciplines and in different formats remains one of the main challenges of modern oncology. Artificial Intelligence (AI) has the po...

MulCNN-HSP: A multi-scale convolutional neural networks-based deep learning method for classification of heat shock proteins.

International journal of biological macromolecules
Heat shock proteins (HSPs) are crucial cellular stress proteins that react to environmental cues, ensuring the preservation of cellular functions. They also play pivotal roles in orchestrating the immune response and participating in processes associ...